diff --git a/gdrive/export_api.py b/gdrive/export_api.py
index b67472a..68b84c1 100644
--- a/gdrive/export_api.py
+++ b/gdrive/export_api.py
@@ -173,7 +173,6 @@ async def find(find: FindModel):
 # ------------------------------- Archive API --------------------------------------
 class InteractionModel(BaseModel):
     interactionId: str
-    driveId: str
 
 
 @router.post("/export/interaction-files")
diff --git a/gdrive/idva/flow_analytics.py b/gdrive/idva/flow_analytics.py
index 55ae826..11a66be 100644
--- a/gdrive/idva/flow_analytics.py
+++ b/gdrive/idva/flow_analytics.py
@@ -76,8 +76,10 @@ def preprocess_report(df: pd.DataFrame) -> pd.DataFrame:
         "twitter",
         "linked.com",
         "lnkd.in",
+        "pllpl",
+        "ffg",
     ]
-    tracked_mediums = ["fb", "cl", "rd", "tx", "ln"]
+    tracked_mediums = ["fb", "cl", "rd", "tx", "ln", "pllpl", "ffg"]
 
     for event in tracked_events:
         tracked_df = df[df[0] == event]
@@ -134,6 +136,8 @@ def create_pivot_tables(df: pd.DataFrame, names_to_id: dict, sheets_id: str):
     twitter_x_pivot(sheets_id, names_to_id, col_dict)
     linkedin_pivot(sheets_id, names_to_id, col_dict)
     linked_pivot(sheets_id, names_to_id, col_dict)
+    pllpl_pivot(sheets_id, names_to_id, col_dict)
+    ffg_pivot(sheets_id, names_to_id, col_dict)
 
     sheets_client.add_pivot_tables(
         sheets_id, names_to_id[SheetsEnum.GSA.value], idva.clicks(col_dict)
@@ -425,6 +429,34 @@ def linked_pivot(sheets_id, names_to_id, col_dict):
     )
 
 
+def pllpl_pivot(sheets_id, names_to_id, col_dict):
+    sheets_client.update_cell_value(
+        sheets_id, SheetsEnum.REKREWT.value, "A23", "PLLPL"
+    )  # Pivot table Label
+
+    sheets_client.add_pivot_tables(
+        sheets_id,
+        names_to_id[SheetsEnum.REKREWT.value],
+        idva.pllpl(col_dict),
+        row_idx=23,
+        col_idx=0,
+    )
+
+
+def ffg_pivot(sheets_id, names_to_id, col_dict):
+    sheets_client.update_cell_value(
+        sheets_id, SheetsEnum.REKREWT.value, "A35", "FFG"
+    )  # Pivot table Label
+
+    sheets_client.add_pivot_tables(
+        sheets_id,
+        names_to_id[SheetsEnum.REKREWT.value],
+        idva.ffg(col_dict),
+        row_idx=35,
+        col_idx=0,
+    )
+
+
 def generate_filename(date: datetime, end_date: datetime = None):
     """
     Return filename for the new spreadsheet to be saved as
diff --git a/gdrive/idva/pivot_director.py b/gdrive/idva/pivot_director.py
index 9faa80f..9146d8b 100644
--- a/gdrive/idva/pivot_director.py
+++ b/gdrive/idva/pivot_director.py
@@ -320,3 +320,79 @@ def linked(self, col_dict: dict) -> dict:
         )
 
         return builder.render()
+
+    def pllpl(self, col_dict: dict) -> dict:
+        builder = PivotTableBuilder(0, col_dict)
+        builder.add_row("eventName", SortOrderEnum.ASCENDING, show_totals=False)
+        builder.add_row("firstUserMedium", SortOrderEnum.ASCENDING)
+        builder.add_row("firstUserSource", SortOrderEnum.ASCENDING)
+        builder.add_row(
+            "firstUserCampaignName", SortOrderEnum.ASCENDING, show_totals=False
+        )
+
+        builder.add_value("eventCount", SummarizeFunctionEnum.SUM)
+
+        # =OR(regexmatch(eventName,"session_start"),regexmatch(eventName,"first_visit"))
+        sessions = FormulaBuilder(
+            FormulaEnum.OR,
+            [
+                FormulaBuilder(
+                    FormulaEnum.REGEX_MATCH,
+                    ["eventName", StringLiteral("session_start")],
+                ),
+                FormulaBuilder(
+                    FormulaEnum.REGEX_MATCH, ["eventName", StringLiteral("first_visit")]
+                ),
+            ],
+        )
+
+        builder.add_filter(
+            "firstUserMedium",
+            FilterTypeEnum.TEXT_CONTAINS,
+            values=[UserEnteredValue("pllpl")],
+        )
+        builder.add_filter(
+            "eventName",
+            FilterTypeEnum.CUSTOM,
+            values=[UserEnteredValue(sessions.render())],
+        )
+
+        return builder.render()
+
+    def ffg(self, col_dict: dict) -> dict:
+        builder = PivotTableBuilder(0, col_dict)
+        builder.add_row("eventName", SortOrderEnum.ASCENDING, show_totals=False)
+        builder.add_row("firstUserMedium", SortOrderEnum.ASCENDING)
+        builder.add_row("firstUserSource", SortOrderEnum.ASCENDING)
+        builder.add_row(
+            "firstUserCampaignName", SortOrderEnum.ASCENDING, show_totals=False
+        )
+
+        builder.add_value("eventCount", SummarizeFunctionEnum.SUM)
+
+        # =OR(regexmatch(eventName,"session_start"),regexmatch(eventName,"first_visit"))
+        sessions = FormulaBuilder(
+            FormulaEnum.OR,
+            [
+                FormulaBuilder(
+                    FormulaEnum.REGEX_MATCH,
+                    ["eventName", StringLiteral("session_start")],
+                ),
+                FormulaBuilder(
+                    FormulaEnum.REGEX_MATCH, ["eventName", StringLiteral("first_visit")]
+                ),
+            ],
+        )
+
+        builder.add_filter(
+            "firstUserMedium",
+            FilterTypeEnum.TEXT_CONTAINS,
+            values=[UserEnteredValue("ffg")],
+        )
+        builder.add_filter(
+            "eventName",
+            FilterTypeEnum.CUSTOM,
+            values=[UserEnteredValue(sessions.render())],
+        )
+
+        return builder.render()